model-selection
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Part of closing #2321 involves updating some of our test arrays to not be constructed from nested iterables where all the internal iterables do not have the same length.
In evalml/tests/model_understanding_tests/test_graphs.py:L374,377,380:
fpr_expected = np.array([[0, 0, 0, 1],
[0, 0, 0, 0.25, 0.75, 1],
[0, 0, 0, 0.5, 1]
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We should add a description to each feature defined in smartcore in the Cargo.toml file, we could use as example the Cargo.toml file of the serde project.
We should add also the documentation for the "serde" feature that currently is not present in the Cargo.toml file.
Not sure if we can u
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Is your feature request related to a problem? Please describe.
Feature is not directly related to a problem, but is rather an enhancement of existing functionality. As suggested by Julian King on the facet Slack channel, we could add Maximum Relevance Minimum Redundancy (MRMR) as a feature selection algorithm.
The algorithm is explained in the following papers:
https://arxiv.org/pdf/1
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